In the past years, the theory and practice of machine learning and data mining have been focused on static and finite data sets from where learning algorithms generate a static m...
We propose a novel system for associating multi-target tracks across multiple non-overlapping cameras by an on-line learned discriminative appearance affinity model. Collecting rel...
In this paper we propose a competition learning approach to coreference resolution. Traditionally, supervised machine learning approaches adopt the singlecandidate model. Neverthe...
Xiaofeng Yang, Guodong Zhou, Jian Su, Chew Lim Tan
In this work a hybrid training scheme for the supervised learning of feedforward neural networks is presented. In the proposed method, the weights of the last layer are obtained em...
We present a new approach to the supervised learning of lateral interactions for the competitive layer model (CLM) dynamic feature binding architecture. The method is based on con...